论文标题
昏迷和田间星系的系统发育分析：一种新的银河发展方法
A phylogenetic analysis of galaxies in the Coma Cluster and the field: a new approach to galaxy evolution
论文作者
论文摘要
我们提出了一种系统发育方法（PA），作为一种新颖而健壮的工具，可以根据其化学成分检测星系人群（GPS）。树的分支被解释为不同的GP，而节点之间的长度为沿分支的内部化学变异。我们使用从斯隆数字天空调查中的30个丰度指数应用于昏迷集群中的475个星系和438个星系中的30个丰度指数。我们发现诸如昏迷之类的密集环境显示了几种GP，这表明环境正在促进星系进化。除红色序列内部的次要结构外，每个人群都具有在颜色幅度空间中可以识别的常见特性。该领域更均匀，呈现一个主要的GP。我们还将主成分分析（PCA）应用于两个样本，发现PCA在识别GPS方面没有相同的功率。
We propose a phylogenetic approach (PA) as a novel and robust tool to detect galaxy populations (GPs) based on their chemical composition. The branches of the tree are interpreted as different GPs and the length between nodes as the internal chemical variation along a branch. We apply the PA using 30 abundance indices from the Sloan Digital Sky Survey to 475 galaxies in the Coma Cluster and 438 galaxies in the field. We find that a dense environment, such as Coma, shows several GPs, which indicates that the environment is promoting galaxy evolution. Each population shares common properties that can be identified in colour magnitude space, in addition to minor structures inside the red sequence. The field is more homogeneous, presenting one main GP. We also apply a principal component analysis (PCA) to both samples, and find that the PCA does not have the same power in identifying GPs.
